Verification of some Commercial CFD Codes on Atypical CFD Problems

Abanto, Juan; Pelletier, Dominique; Garon, André; Trépanier, Jean‐Yves; Reggio, Marcelo

doi:10.2514/6.2005-682

Cited by 16 publications

(6 citation statements)

References 2 publications

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“…The importance of numerical verification should not be taken for granted, whether it is a locally-developed computational fluid dynamics (CFD) solver or a commercial package. Indeed, Abanto et al [35] showed that three commonly used commercial CFD codes (Fluent, CFX, and TASCFlow) did not display monotonic error convergence for very simple, two-dimensional test problems for which analytical solutions are easily derived from the Navier-Stokes equations.…”

Section: Verificationmentioning

confidence: 98%

“…Because a commercial code, or any code for that matter, may not be numerically wellbehaved [35], code verification is essential. In this work, the MMS approach was used to perform the code verification of STAR-CCM+ for the constant-density, unfiltered governing equations [36] and the accompanying CFD algorithm.…”

Section: Code Verification Using Mms With 2d Laminar Problemmentioning

confidence: 99%

See 1 more Smart Citation

Application of a Verification, Validation and Uncertainty Quantification Framework to a Turbulent Buoyant Helium Plume

Jatale

Smith

Thornock

et al. 2015

Flow Turbulence Combust

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A framework for verification and validation/uncertainty quantification of largescale, highly coupled, complex processes is presented. Steps in the framework include code and solution verification, development of an input/uncertainty map, definition of evaluation criteria, development of a surrogate model, performance of a consistency analysis (a mathematical statement limiting error), and the feed forward and feedback of information gain from the analysis. This framework is applied to a turbulent, buoyant, 1 m diameter helium plume. Experimental measurements are obtained from Sandia National Laboratory while the helium plume simulations are performed using Large Eddy Simulation. Both parameter and experimental uncertainty associated with the helium plume are reduced by requiring consistency.

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Section: Verificationmentioning

confidence: 98%

Section: Code Verification Using Mms With 2d Laminar Problemmentioning

confidence: 99%

Application of a Verification, Validation and Uncertainty Quantification Framework to a Turbulent Buoyant Helium Plume

Jatale

Smith

Thornock

et al. 2015

Flow Turbulence Combust

View full text Add to dashboard Cite

show abstract

“…The order of grid convergence describes the behaviour of the solution error E as a function of mesh element size h [32], i.e. A convergence study was performed in this paper to compute the L 2 error for various Péclet numbers using the characteristic Galerkin method.…”

Section: Mesh Convergence Properties Of the Lcg Methodsmentioning

confidence: 99%

An element‐wise, locally conservative Galerkin (LCG) method for solving diffusion and convection–diffusion problems

Thomas

Nithiarasu

2007

Numerical Meth Engineering

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SUMMARYAn element-wise locally conservative Galerkin (LCG) method is employed to solve the conservation equations of diffusion and convection-diffusion. This approach allows the system of simultaneous equations to be solved over each element. Thus, the traditional assembly of elemental contributions into a global matrix system is avoided. This simplifies the calculation procedure over the standard global (continuous) Galerkin method, in addition to explicitly establishing element-wise flux conservation. In the LCG method, elements are treated as sub-domains with weakly imposed Neumann boundary conditions. The LCG method obtains a continuous and unique nodal solution from the surrounding element contributions via averaging. It is also shown in this paper that the proposed LCG method is identical to the standard global Galerkin (GG) method, at both steady and unsteady states, for an inside node. Thus, the method, has all the advantages of the standard GG method while explicitly conserving fluxes over each element.Several problems of diffusion and convection-diffusion are solved on both structured and unstructured grids to demonstrate the accuracy and robustness of the LCG method. Both linear and quadratic elements are used in the calculations. For convection-dominated problems, Petrov-Galerkin weighting and highorder characteristic-based temporal schemes have been implemented into the LCG formulation.

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“…Code verification is appropriate during code development phases and not considered herein; however, shortcomings have been observed [25] in some cases. Solution V&V provides error/ uncertainty estimates for a single user/code/simulation/setup resulting in fixed estimates analogous to experimental systematic uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Statistical Approach for Computational Fluid Dynamics State-of-the-Art Assessment: N-Version Verification and Validation

Stern

Diez

Sadat-Hosseini

et al. 2017

Journal of Verification, Validation and Uncertainty Quantification

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A statistical approach for computational fluid dynamics (CFD) state-of-the-art (SoA) assessment is presented for specified benchmark test cases and validation variables, based on the combination of solution and N-version verification and validation (V&V). Solution V&V estimates the systematic numerical and modeling errors/uncertainties. N-version verification estimates the random simulation uncertainty. N-version validation estimates the random absolute error uncertainty, which is combined with the experimental and systematic numerical uncertainties into the SoA uncertainties and then used to determine whether or not the individual codes/simulations and the mean code are N-version validated at the USoAi and USoA intervals, respectively. The scatter is due to differences in models and numerical methods, grid types, domains, boundary conditions, and other setup parameters. Differences between codes/simulations and implementations are due to myriad possibilities for modeling and numerical methods and their implementation as CFD codes and simulation applications. Industrial CFD codes are complex software with many user options such that even in solving the same application, different results may be obtained by different users, not necessarily due to user error but rather the variability arising from the selection of various models, numerical methods, and setup options. Examples are shown for ship hydrodynamics applications using results from the Seventh CFD Ship Hydrodynamics and Second Ship Maneuvering Prediction Workshops. The role and relationship of individual code solution V&V versus N-version V&V and SoA assessment are discussed.

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Verification of some Commercial CFD Codes on Atypical CFD Problems

Cited by 16 publications

References 2 publications

Application of a Verification, Validation and Uncertainty Quantification Framework to a Turbulent Buoyant Helium Plume

Application of a Verification, Validation and Uncertainty Quantification Framework to a Turbulent Buoyant Helium Plume

An element‐wise, locally conservative Galerkin (LCG) method for solving diffusion and convection–diffusion problems

Statistical Approach for Computational Fluid Dynamics State-of-the-Art Assessment: N-Version Verification and Validation

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